Despite substantial gender convergence over the last century, there is still considerable gender inequality in labour market outcomes in all developed countries. Evidence from different high-income countries suggests that most of the remaining gender inequality can be explained by the unequal impacts of parenthood on men and women (e.g. Waldfogel 1998; Paull 2008; Bertrand et al. 2010; Goldin 2014; Angelov et al. 2016; Kleven et al. 2016). For example, Kleven et al. (2016) show that 80% of the remaining earnings inequality between men and women in Denmark results from ‘child penalties’ faced by mothers, but not fathers. A variety of underlying mechanisms may be at play—from traditional stories focusing on comparative advantage and the gains from specialization to more behavioural stories focusing on social norms—but the evidence suggests that these mechanisms operate primarily through the impacts of children.
The aforementioned studies analyse gender inequality in countries that have already experienced the demographic transition, which reduced the fertility rate per woman from around 5–6 to around 2. The large child penalties observed in these countries—about 10% of female earnings per child in Denmark—naturally place the demographic transition at centre stage of the historical gender convergence in industrialized nations. Indeed, theories of economic growth and fertility highlight the demographic transition as a key transmission mechanism for gender convergence (e.g. Galor and Weil 1996; Galor 2012). In these theories, technological progress and capital accumulation complement mentally-intensive tasks more than physically-intensive tasks in production, thus favouring the skill in which women have a comparative advantage. This increases the labour market productivity of women and therefore the opportunity cost of raising children—the child penalty—inducing women to have fewer children and increase their labour supply and earnings. An additional mechanism is that technological growth directly increases the returns to human capital investments, leading parents to substitute from child quantity to child quality, and further spurring the demographic transition and bringing women to the labour market. These theories have two implications: (i) children and education are the key factors in gender convergence, and (ii) the female penalty per child can be high in advanced countries due to the large investments in child quality.
In this descriptive paper we bring new evidence to bear on these questions. The contribution of our paper lies partly in the data gathering exercise: we have assembled micro datasets containing information on gender, earnings, labour supply, age, children, education and gender attitudes for a large set of countries over time. Our analysis is based on a collection of 248 surveys between 1967 and 2014, covering 53 countries across a wide range of income levels. This allows us to document how gender inequality evolves across levels of economic development and explore potential causes for this evolution. Our paper complements a voluminous literature on gender gaps in the labour market, which provides evidence from specific countries or from across high-income countries. Reviews of this literature have been provided by, for example, Altonji and Blank (1999), Bertrand (2011), Blau and Kahn (2016), and Olivetti and Petrongolo (2016).
We begin by documenting the evolution of gender inequality in earnings over the development path, and then decompose these changes into the three underlying components: labour force participation, hours worked, and wage rates. Gender inequality in earnings falls substantially with development, from a gender gap of around 65% at low income levels to a gender gap of around 35% at high income levels. We show that the convergence of earnings is driven by participation and wage rates, but not hours. In particular, female labour force participation increases dramatically with development, and as a result the participation gap falls from 50% to 5–10% as GDP per capita rises. At the same time, gender differences in hours worked (conditional on working) are relatively small and very stable, thus contributing very little to changes in earnings inequality.
Turning to the potential causes of these changes, we first focus on the role of children and the implications of demographic transition. Considering women of childbearing age (16–40 years), there is a very large difference between those who have children and those who do not. For women without children, the gender gap in earnings is about 25% and stable across levels of development. For women with children, the gender gap is much larger and falls with development, from about 70% to about 50%. While the difference in levels between these two series is directly suggestive of the importance of children, the within-series changes are also informative. In particular, the within-group changes in gender inequality are much smaller than the aggregate change, which implies that the observed decline in aggregate gender inequality can be explained largely by a compositional change from those with children to those without children. Indeed, the fraction of women of childbearing age who have children falls strongly over the development path, both because more women do not have any children and because women have children later.1
We also consider the role of education. As has been documented elsewhere, there has been an enormous increase in female education, to the point where more women than men take college degrees in a number of countries (Goldin et al. 2006; Becker et al. 2010). In our sample of 53 countries, we show that women are now more college educated than men in the vast majority of high- and middle-income countries. Across levels of development, the gender gap in the fraction with college degrees falls from + 5 percentage points to − 8 percentage points, and turns negative at a per capita GDP level of about $25,000. While these education changes can explain some of the decline in earnings inequality between men and women, they explain much less than children. We argue that there are two reasons for this. The first is that the variation in relative education between men and women across development levels is small compared to the variation in fertility. The second is that the impact of education is dampened by children, because even highly educated women face large child penalties when they become parents (see also Bertrand et al. 2010; Wilde et al. 2010; Kleven et al. 2016).
Finally, we present evidence on gender attitudes over the path of development, focusing in particular on the attitudes towards working women with children. As GDP per capita increases, these attitudes change quite dramatically. For example, there is a strong decline in the fraction of people who believe that children are negatively affected by having working mothers. Similarly, there is a strong decline in the fraction of people who believe that women with young children ought to stay at home rather than working part-time or full-time, whereas at the same time the views on women without children or women whose children have left home are relatively stable across levels of development. Of course, the fact that these norms change with development does not necessarily mean that they are causally affecting the patterns described above, although a recent and growing literature suggests that social norms may in fact impact gender differences in labour market outcomes (for a review, see Bertrand 2011). The most intriguing aspect of our descriptive findings is perhaps the differential evolution of attitudes towards women with and without children. Consistent with our other findings, this suggests that the evolution of gender inequality should be analysed and interpreted to a large degree through the prism of motherhood and fertility.
The paper is organized as follows. Section 'Data and Methods' describes the data and empirical approach, Section 'Gender Inequality Across Levels of Development: Basic Facts' documents some basic facts on gender inequality and development, Section 'Gender Inequality Across Levels of Development: Proximate Causes' explores some possible causes for the observed patterns, and Section 'Conclusion' concludes.